Decentralized and Dynamic Bandwidth Allocation in Networked Control Systems Ahmad T. Al-Hammouri, Michael S. Branicky, Vincenzo Liberatore Case Western Reserve University Stephen M. Phillips Arizona State University April 25, 2006 Support by: NSF CCR-0329910, Department of Commerce TOP 39-6004003, NASA NNC04AA12A, and an OhioICE Training grant
Paper Overview Control over Networks NCSs, DCSs, SANETs, …
Control of Networks Efficient BW allocation Congestion control
Fairness
We propose a “Cof N” scheme to better serve “Cover N” Ahmad Al-Hammouri
Decentralized and Dynamic Bandwidth Allocation in Networked Control Systems (WPDRTS’06)
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Control over Networks
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Decentralized and Dynamic Bandwidth Allocation in Networked Control Systems (WPDRTS’06)
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Control over Networks
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Control over Networks
Ahmad Al-Hammouri
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Control over Networks
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Control over Networks
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Decentralized and Dynamic Bandwidth Allocation in Networked Control Systems (WPDRTS’06)
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Control over Networks
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Control over Networks
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Control over Networks
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Control over Networks
Ahmad Al-Hammouri
Decentralized and Dynamic Bandwidth Allocation in Networked Control Systems (WPDRTS’06)
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Control over Networks Remote interaction (monitoring & control) with the physical world Applications:
Industrial automation & process control Space exploration, e.g., telerobotics Smart homes Medical sensing & surgical simulations Automatic asset mgmt. (RFID) Ahmad Al-Hammouri
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Control of Networks (Scope of the paper) A bandwidth allocation scheme Objectives:
Stability of control systems Efficiency & fairness Fully distributed, asynchronous, & scalable Dynamic & self reconfigurable
Formulating the scheme in CT NCSs regulate h based on congestion fed back from the network Ahmad Al-Hammouri
Decentralized and Dynamic Bandwidth Allocation in Networked Control Systems (WPDRTS’06)
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Sampling Rate & Network Congestion h=1/r
Ahmad Al-Hammouri
Decentralized and Dynamic Bandwidth Allocation in Networked Control Systems (WPDRTS’06)
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Sampling Rate & Network Congestion
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Problem Formulation Define a utility fn U(r) that is Monotonically increasing Strictly concave Defined for r ≥ rmin
Optimization formulation max ∑ i Ui (ri ) s.t.
∑
i∈S ( l )
ri ≤ Cl , l = 1,..., L
and ri ≥ r min, i Ahmad Al-Hammouri
Decentralized and Dynamic Bandwidth Allocation in Networked Control Systems (WPDRTS’06)